Title: Jump robust daily covariance estimation by disentangling variance and correlation components
Authors: Boudt, Kris ×
Cornelissen, Jonathan
Croux, Christophe #
Issue Date: 2012
Publisher: North-Holland Pub. Co.
Series Title: Computational Statistics & Data Analysis vol:56 issue:11 pages:2993-3003
Abstract: A jump robust positive semidefinite rank-based estimator for the daily covariance matrix based on high-frequency intraday returns is proposed. It disentangles covariance estimation into variance and correlation components. This allows us to account for non-synchronous trading by estimating correlations over lower sampling frequencies. The efficiency gain of disentangling covariance estimation and the jump robustness of the estimator are illustrated in a simulation study. In an application to the Dow Jones Industrial Average constituents, it is shown that the proposed estimator leads to more stable portfolios.
ISSN: 0167-9473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Research Center Finance, Leuven
Leuven Statistics Research Centre (LStat)
Faculty of Economics and Business (FEB) - miscellaneous
Department of Financial Management, Campus Carolus Antwerp
× corresponding author
# (joint) last author

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